Statistical Evaluation of Diagnostic Performance: Topics in ROC Analysis

Introduction
Background and Introduction
Background Information
Gold Standard, Decision Threshold, Sensitivity, and Specificity
Kappa Statistics
Receiver Operating Characteristic Curve
Area and Partial Area under ROC Curve
Confidence Intervals, Regions, and Bands
Point of Intersection and Youden Index
Comparison of Two or More ROC Curves
Approaches to ROC Analysis
References

Methods for Univariate and Multivariate Data
Diagnostic Rating Scales
Introduction
Interpreter-Free Diagnostic Systems.
Human Interpreter as Integral Part of Diagnostic System
Remarks and Further Reading.
References
Monotone Transformation Models
Introduction
General Assumptions
Empirical Methods
Nonparametric Kernel Smoothing
Parametric Models and Monotone Transformations to Binormal Distributions
Confidence Intervals
Concordance Measures in Presence of Monotone Transformations
Intraclass Correlation Coefficient
Remarks and Further Reading
References
Combination and Pooling of Biomarkers
Introduction
Combining Biomarkers to Improve Diagnostic Accuracy
ROC Curve Analysis with Pooled Samples
Remarks and Further Reading
References
Bayesian ROC Methods
Introduction
Methods for Sensitivity, Specificity, and Prevalence
Clustered Data Structures and Hierarchical Methods
Assumptions and Models for ROC Analysis
Normality Transformation
Elicitation of Prior Information
Estimation of ROC Parameters and Characteristics
Remarks and Further Reading
References

Advanced Approaches and Applications
Sequential Designs of ROC Experiments
Introduction
Group Sequential Tests Using Large Sample Theory
Sequential Evaluation of Single ROC Curve
Sequential Comparison of Two ROC Curves
Sequential Evaluation of Binary Outcomes
Sample Size Estimation
Remarks and Further Reading
References
Multireader ROC Analysis
Introduction
Overall ROC Curve and Its AUC
Statistical Analysis of Cross-Correlated Multireader Data
Remarks and Further Reading
References
Appendix 7.A: Closed Form Formulation of DBM Approach for Comparing Two Modalities Using Empirical AUC
Appendix 7.B: Variance Estimators of Empirical AUCs
Free-Response ROC Analysis
Introduction
FROC Approach
Other Approaches of Detection–Localization Performance Assessment Remarks and Further Reading References
Machine Learning and Predictive Modeling
Introduction
Predictive Modeling
Cross-Validation
Bootstrap Resampling Methods
Overfitting and False Discovery Rate
Remarks and Further Reading
References

Discussions and Extensions
Summary and Challenges
Summary and Discussion
Future Directions in ROC Analysis
Future Directions in Reliability Analysis
Final Remarks

Section Appendices Symbols, Notations and Assumptions
Appendix A: Conventions
Appendix B: Notations
Appendix C: Abbreviations
Appendix D: Definitions and Terminologies
Appendix E: Remarks
Index